Sunghwan Joo

424 total citations
12 papers, 176 citations indexed

About

Sunghwan Joo is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sunghwan Joo has authored 12 papers receiving a total of 176 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Electrical and Electronic Engineering, 4 papers in Artificial Intelligence and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sunghwan Joo's work include Adversarial Robustness in Machine Learning (3 papers), Radio Frequency Integrated Circuit Design (2 papers) and Advanced Memory and Neural Computing (2 papers). Sunghwan Joo is often cited by papers focused on Adversarial Robustness in Machine Learning (3 papers), Radio Frequency Integrated Circuit Design (2 papers) and Advanced Memory and Neural Computing (2 papers). Sunghwan Joo collaborates with scholars based in South Korea and United Kingdom. Sunghwan Joo's co-authors include Taesup Moon, Hyoseop Lee, Wonjong Rhee, Seong‐Ook Jung, Juyeon Heo, Sumin Lee, Tae Woo Oh, Dohyung Kim, Junghyup Lee and Jongsoo Lee and has published in prestigious journals such as IEEE Access, IEEE Journal of Solid-State Circuits and IEEE Sensors Journal.

In The Last Decade

Sunghwan Joo

12 papers receiving 174 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sunghwan Joo South Korea 7 133 35 34 31 21 12 176
Haimonti Dutta India 7 36 0.3× 12 0.3× 28 0.8× 26 0.8× 13 0.6× 16 130
Chris Hermans Belgium 8 73 0.5× 27 0.8× 28 0.8× 24 0.8× 13 0.6× 22 216
James Paris United States 10 149 1.1× 16 0.5× 102 3.0× 8 0.3× 4 0.2× 17 205
Jean-Charles Le Bunetel France 7 276 2.1× 14 0.4× 61 1.8× 3 0.1× 8 0.4× 17 295
Kai-Chun Chu China 5 87 0.7× 8 0.2× 14 0.4× 14 0.5× 13 0.6× 16 143
Srivatsan Srinivasan United States 5 15 0.1× 17 0.5× 40 1.2× 13 0.4× 20 1.0× 15 113
Ayoob Alateeq Saudi Arabia 10 220 1.7× 4 0.1× 80 2.4× 34 1.1× 4 0.2× 29 271
Yuhang Guo China 9 20 0.2× 33 0.9× 6 0.2× 98 3.2× 6 0.3× 40 217
Mengting Li China 9 224 1.7× 4 0.1× 23 0.7× 11 0.4× 12 0.6× 39 297

Countries citing papers authored by Sunghwan Joo

Since Specialization
Citations

This map shows the geographic impact of Sunghwan Joo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sunghwan Joo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunghwan Joo more than expected).

Fields of papers citing papers by Sunghwan Joo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunghwan Joo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sunghwan Joo. The network helps show where Sunghwan Joo may publish in the future.

Co-authorship network of co-authors of Sunghwan Joo

This figure shows the co-authorship network connecting the top 25 collaborators of Sunghwan Joo. A scholar is included among the top collaborators of Sunghwan Joo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sunghwan Joo. Sunghwan Joo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Joo, Sunghwan, et al.. (2023). Towards More Robust Interpretation via Local Gradient Alignment. Proceedings of the AAAI Conference on Artificial Intelligence. 37(7). 8168–8176. 3 indexed citations
2.
Kim, Ji Young, et al.. (2022). A 5 Gb/s Time-Interleaved Voltage-Mode Duobinary Encoding Scheme for 3-D-Stacked IC. IEEE Journal of Solid-State Circuits. 57(6). 1913–1923. 5 indexed citations
3.
Lee, Sumin, Ki-Beom Lee, Sunghwan Joo, et al.. (2022). SIF-NPU: A 28nm 3.48 TOPS/W 0.25 TOPS/mm2 CNN Accelerator with Spatially Independent Fusion for Real-Time UHD Super-Resolution. 97–100. 6 indexed citations
4.
Lee, Sumin, et al.. (2021). CNN encryption using XOR Gate for Hardware Optimization. 359–360. 3 indexed citations
5.
Joo, Sunghwan, Tae Woo Oh, Ji Young Kim, et al.. (2021). Highly Accurate, Fully Digital Temperature Sensor With Curvature Correction. IEEE Sensors Journal. 21(19). 21248–21258. 2 indexed citations
6.
Lee, Sumin, et al.. (2020). CNN Acceleration With Hardware-Efficient Dataflow for Super-Resolution. IEEE Access. 8. 187754–187765. 10 indexed citations
7.
Heo, Juyeon, Sunghwan Joo, & Taesup Moon. (2019). Fooling Neural Network Interpretations via Adversarial Model Manipulation. arXiv (Cornell University). 32. 2921–2932. 11 indexed citations
8.
9.
Joo, Sunghwan, et al.. (2019). Subtask Gated Networks for Non-Intrusive Load Monitoring. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 1150–1157. 96 indexed citations
10.
11.
Joo, Sunghwan, et al.. (2018). Comparative analysis of MCU memory for IoT application. 1–3. 6 indexed citations
12.
Joo, Sunghwan, et al.. (2016). Intelligent Classification and Context Analysis System of Voice Data. 162–163. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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